Corporate Overview
May 10th , 2024
NASDAQ: LTRN
Forward Looking Statements
This presentation contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section
21E of the Securities Exchange Act of 1934, as amended. These forward-looking statements include, among other things, statements relating to: future events or our future financial performance; the potential advantages of our RADR® platform in identifying drug candidates and patient populations that are likely to respond to a drug candidate; our strategic plans to advance the development of our drug candidates and antibody drug conjugate (ADC) development program; estimates regarding the development timing for our drug candidates and ADC development program; expectations and estimates regarding clinical trial timing and patient enrollment; our research and development efforts of our internal drug discovery programs and the utilization of our RADR® platform to streamline the drug development process; our intention to leverage artificial intelligence, machine learning and genomic data to streamline and transform the pace, risk and cost of oncology drug discovery and development and to identify patient populations that would likely respond to a drug candidate; estimates regarding patient populations, potential markets and potential market sizes; sales estimates for our drug candidates and our plans to discover and develop drug candidates and to maximize their commercial potential by advancing such drug candidates ourselves or in collaboration with others. Any statements that are not statements of historical fact (including, without limitation, statements that use words such as "anticipate," "believe," "contemplate," "could," "estimate," "expect," "intend," "seek," "may," "might," "plan," "potential," "predict," "project," "target," "model," "objective," "aim," "upcoming," "should," "will," "would," or the negative of these words or other similar expressions) should be considered forward-looking statements. There are a number of important factors that could cause our actual results to differ materially from those indicated by the forward-looking statements, such as (i) the risk that our research and the research of our collaborators may not be successful, (ii) the risk that promising observations in preclinical studies do not ensure that later studies and development will be successful, (iii) the risk that we may not be successful in licensing potential candidates or in completing potential partnerships and collaborations, (iv) the risk that none of our product candidates has received FDA marketing approval, and we may not be able to successfully initiate, conduct, or conclude clinical testing for or obtain marketing approval for our product candidates, (v) the risk that no drug product based on our proprietary RADR® AI platform has received FDA marketing approval or otherwise been incorporated into a commercial product, and (vi) those other factors set forth in the Risk Factors section in our Annual Report on Form 10-K for the year ended December 31, 2023, filed with the Securities and Exchange Commission on March 18, 2024. You may access our Annual Report on Form 10-K for the year ended December 31, 2023 under the investor SEC filings tab of our website at www.lanternpharma.com or on the SEC's website
at www.sec.gov. Given these risks and uncertainties, we can give no assurances that our forward-looking statements will prove to be accurate, or that any other results or events projected or contemplated by our forward-looking statements will in fact occur, and we caution investors not to place undue reliance on these statements. All forward-looking statements in this presentation represent our judgment as of the date hereof, and, except as otherwise required by law, we disclaim any obligation to update any forward-looking statements to conform the statement to actual results or changes in our expectations.
NASDAQ: LTRN | 1 |
Lantern's AI platform, RADR®, is transforming the cost, pace, and timeline of cancer drug discovery and development
12 | 5 |
Lead drug programs* | Clinical stage lead |
powered by AI | drug candidates* |
100+ | $38.4M** |
Issued patents & | Cash/cash eq./ |
pending applications | marketable securities |
2.5 years | $1.5M |
Avg. time for new | Avg. cost for new |
LTRN programs | LTRN programs |
to Ph. 1 Trial | to Ph. 1 Trial |
- Includes drug programs being developed in collaboration
- at 3/31/2024
2
*
Current Challenges
Only 6%
of clinical trials using traditional drug discovery approaches succeed
Costly
Risky
Slow
Average cost to bring a new cancer drug to market is $2.8 billion
Out of 20,000 trials from 2012-2022,
19,200 trials failed
Early-Stage development takes 3-5+Years, late-stage development takes 6-12+Years
*Clinical Development Success Rates
and Contributing Factors 2011-2020, BIO Stats
Current oncology drug development is being improved by data-driven, and AI-enabledapproaches and technology
3
Lantern is Transforming Drug Discovery Timelines & Costs with AI
AI insights and biomarkers can increase the odds of clinical trial success by 12X*
(*Parker et al., 2021)
RADR® can predict and stratify real-world patients for clinical trials with 88% accuracy
Lantern can compress the timeline of early-stagedrug development by 70% and reduce the cost by 80%
Lantern has launched 10 new programs in 2 years, and has active ongoing ph.1 and ph.2 clinical trials
LANTERN'S DRUG DEVELOPMENT MODEL AND OBJECTIVES
Large Scale/Multi-omics | Proprietary AI | Accelerated |
timelines; reduced | ||
Oncology Data | platform RADR® | costs and risks |
4
Lantern's AI-Driven Business Model has Multiple Routes Towards Success
Areas of Focus
1 Rescue &
Reposition
Drug Candidates
2 Discover
& Develop
New Molecules
Including ADCs
AI Platform
3 Accelerate
& De-risk
Trials with
Biopharma Partners
Successes to Date
Based on previous clinical data and observations, LP-300was rescued for never smokers with NSCLC and is in a Phase 2 trial
LP-284'sunique mechanism of action was predicted by RADR® and was developed to Phase 1 trial in 2 years
Predicting patient response with greater than 88% accuracy, Lantern is accelerating the development ofElraglusib
High-value | |
Targeted | Partnering |
& Licensing | |
Clinical Trials | Opportunities |
By Lantern and/or other | With biopharma and |
biopharma partners | tech companies |
5
Response Algorithm for Drug Positioning & Rescue
A proprietary integrated data analytics, experimental biology, oncology- focused, machine-learning-based platform focused on drug development
60+ Billion
Data points from oncology focused real-world patient and clinical data and preclinical studies
80%+
Prediction
Success
130K+
Patient
Records
200+
Advanced ML Algorithms
8,163+
Data Sets
AI-Powered RADR® Modules for Oncology Drug Discovery and Development
m1 | Discover mechanism | ||
of action of any | m5 | Characterize specialized | |
compound or drug | attributes of a molecule | ||
Identify/prioritize a | such as BBB permeability | ||
m2 | |||
compound's disease | Enhance the selection | ||
indications or subtypes | m6 | ||
of optimal combination | |||
m3 | Determine optimal | of ADC components | |
drug combos to improve | |||
therapeutic potential | Discover drug combos for | ||
m7 | |||
m4 | Generate ML-driven | checkpoint inhibitors to | |
biomarker signatures | improve therapeutic index | ||
for patient selection |
6
Lantern Pharma is a Top 10 End-to-End AI Drug Discovery Company
According to Deep Pharma Intelligence (May 04, 2022)
NASDAQ: LTRN | 7 |
RADR®'s AI Framework
RADR®'s AI framework develops actionable insights using billions of datapoints
Data sources/Datatypes | 200+ AI Algorithms |
RADR® Modules (m)
m1 MoA Discovery
Clinical Trials
In vitro/ In vivo
Studies
Genetic
Screens/Panels
Chemical Structure
Collaborator Studies
Multi-Omics
Drug Response
Public/Private
Repositories
Ensemble
Deep Learning
Bayesian Based
Tree Based
Rule Based
Clustering
Others
m2
RADR AI insights
m3
m4
m5
m6
m7
Disease Indication Identification
Drug Combination Optimization
Biomarker Signature Generation
Molecule attribute Characterization
ADC Development
Immune Checkpoint Inhibitor Development
NASDAQ: LTRN | 8 |
RADR® Case Study - Actuate Therapeutics
Advanced RADR® machine learning models predict clinical trial patient responses at 88% accuracy
x
-
Predicted patient response with greater than
88% accuracy - Identified metastatic melanoma patients resistant to PD-1 therapies may benefit from Elraglusib
- Insights and new data including RNA, ctDNA, and protein biomarkers are informing design of an upcoming Phase 2 clinical trial
- Lantern received equity in Actuate as part of the collaboration
Lantern is accelerating the development of Actuate Therapeutic's drug candidate, Elraglusib* (9-ING-41), using AI insights produced by RADR®
Model generation for patient response prediction
Posters:
*Elraglusib is a widely researched GSK-3β inhibitor. Currently, Elraglusib is in multiple active Phase I/II clinical trials as a monotherapy and in combination with other agents (NCT03678883)
NASDAQ: LTRN | 9 |
Attachments
- Original Link
- Original Document
- Permalink
Disclaimer
Lantern Pharma Inc. published this content on 13 May 2024 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 13 May 2024 15:30:21 UTC.